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Abstract

The CD8+ T cell response is a critical component of antiviral immunity, particularly in hosts who are immunocompromised or undergoing B cell-depleting therapy, such as rituximab. As viral evolution can lead to escape from CD8+ T cell recognition, tools that predict such escape are increasingly relevant. Here, we present CD8scape, an accessible command-line tool designed to predict viral escape from the CD8+ T cell response based on within-host sequence variation and HLA class I genotype. CD8scape is primarily a Julia wrapper for NetMHCpan v4.2, a neural network-based predictor trained on mass spectrometry-derived peptide presentation data. CD8scape integrates variant data and viral reading frames to identify all overlapping 8-11mer peptides at variant sites in both ancestral and derived states. These peptides are evaluated using NetMHCpan, which outputs eluted ligand (EL) scores as allele-specific percentile ranks to account for differences in MHC binding fastidiousness, and these are passed back to CD8scape itself. For each variant, the best-ranking peptide across all alleles is identified, and a harmonic mean is used to summarize presentation likelihood across the hosts HLA genotype. A fold-change between ancestral and derived harmonic means quantifies the likelihood of immune escape, with values >1 indicating reduced predicted presentation, and therefore a potential escape from the CD8+ T cell response. This is converted to a log2 value of this fold-change so that the metric is symmetric around 0, with positive values representing predicted escape. CD8scape can operate with known HLA genotypes or a representative HLA supertype panel for generalizable predictions. We demonstrate our method by application to within-host SARS-CoV-2 evolution in a rituximab-treated patient and discuss its implications for population-level CD8+ T cell escape.

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